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Introduction¶
In diesem Notebook wenden wir Applied Machine Learning (AML) Techniken an, um effektive Strategien für personalisierte Kreditkarten-Werbekampagnen zu entwickeln. Unser Ziel ist es, mithilfe von Kunden- und Transaktionsdaten präzise Modelle zu erstellen, die die Wahrscheinlichkeit des Kreditkartenkaufs vorhersagen.
Lib Importing¶
Load the Data¶
EDA¶
Account¶
| account_id |
district_id |
frequency |
date |
| Loading... (need help?) |
Card¶
| card_id |
disp_id |
type |
issued |
| Loading... (need help?) |
Client¶
| client_id |
birth_number |
district_id |
| Loading... (need help?) |
Disp¶
| disp_id |
client_id |
account_id |
type |
| Loading... (need help?) |
District¶
| A1 |
A2 |
A3 |
A4 |
A5 |
A6 |
A7 |
A8 |
A9 |
A10 |
A11 |
A12 |
A13 |
A14 |
A15 |
A16 |
| Loading... (need help?) |
Loan¶
| loan_id |
account_id |
date |
amount |
duration |
payments |
status |
| Loading... (need help?) |
Order¶
| order_id |
account_id |
bank_to |
account_to |
amount |
k_symbol |
| Loading... (need help?) |
Trans¶
| trans_id |
account_id |
date |
type |
operation |
amount |
balance |
k_symbol |
bank |
account |
| Loading... (need help?) |
Account¶
Card¶
Client¶
Disp¶